Adaptive Fourier analysis using a variable step-size LMS algorithm

Abstract

Adaptive Fourier analysis has numerous applications in biomedical engineering, music signal processing, digital communications, power engineering etc. So far, a lot of adaptive algorithms and systems have been developed and applied. In this paper, a variable step-size LMS (VSS-LMS) algorithm is proposed for adaptive Fourier analysis of noisy sinusoidal signals. It significantly outperforms the conventional LMS and p-power algorithms in both stationary and nonstationary environments at the expense of very little increase in computational cost. Extensive simulations as well as application to real noise signals generated by large-scale factory rotating machines are conducted to confirm the improved performance and tracking capabilities of the proposed algorithm.